code: def forward(self, img_local, is_flip=False):
      if is_flip:
          img_local = img_local.flip([3])
      pred = self.backbone(img_local)
      pred1 = pred[:, : 1220 * 3]
      pred2 = pred[:, 1220 * 3 : 1220 * 5]
      meta = {"flip": is_flip}
      if not self.use_eyes:
          return pred1, pred2, meta
      else:
          eye_verts = pred[:, 1220 * 5 : 1220 * 5 + 481 * 2 * 3]
          eye_points = pred[:, 1220 * 5 + 481 * 2 * 3 :]
          return pred1, pred2, meta, eye_verts, eye_points
  
imports: import os
  import time
  import timm
  import glob
  import numpy
  import os.path
  import cv2
  import torch
  import torch.distributed
  from torch import nn
  from pathlib import Path
  from backbones import get_network
  from skimage import transform
  from scipy.spatial.transform import Rotation
label_desc: Use image node_id 4 for calling the JMLRInference obj's underlying member method code with example usage: obj.forward(img_local, is_flip) and returns: pred1,  pred2,  meta, pred1,  pred2,  meta,  eye_verts,  eye_points